Segmentation of the Common Carotid Intima-Media Complex in Ultrasound Images Using 2-D Continuous Max-Flow and Stacked Sparse Auto-encoder |
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| Institution: | 2. School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, China;3. Chinese Medical Hospital of Wujin, Changzhou, Jiangsu, China;4. Department of Mathematics, Nanjing University, Nanjing, Jiangsu, China;2. Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario, Canada;3. Stroke Prevention and Atherosclerosis Research Centre, Robarts Research Institute, Western University, London, Ontario, Canada;4. Medical Ultrasound Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China;5. Department of Cardiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China;1. Division of Cardiovascular Medicine, Toho University Ohashi Medical Center, 2-17-6 Ohashi Meguro-ku, Tokyo, Japan;2. Point of Care Devices, Global Biomedical Technologies, Inc., Roseville, CA, USA;3. Cardiovascular Medicine, University of Virginia, VA, USA\n;4. Department of Radiology, Brain and Mind Research Institute, Weill Cornell Medical College, NY, USA;5. CorVasc Vascular Laboratory, 8433 Harcourt Rd #100, Indianapolis, IN, USA;6. IMIM - Hospital del Mar, PasseigMarítim 25-29, Barcelona, Spain;7. Division of Cardiovascular Medicine, Centre for Global Health and Medicine (NCGM), 1-21-1 Toyama Shinjuku-ku, Tokyo, Japan;8. Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari – Polo di Monserrato, Università di Cagliari, s.s. 554 Monserrato, Cagliari 09045, Italy\n;9. UC Davis Vascular Center, University of California, Davis, CA, USA;10. Vascular Screening and Diagnostic Centre, London, and Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus;11. Diagnostic and Monitoring Division, AtheroPoint™ LLC, Roseville, CA, USA;12. Electrical Engineering Department (Aff.), Idaho State University, ID, USA;2. Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy;3. Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy |
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| Abstract: | The intima-media thickness (IMT) of a common carotid artery in an ultrasound image is considered an important indicator of the onset of atherosclerosis. However, it is challenging to segment the intima-media complex (IMC) directly in ultrasound images. This study proposes a fully automatic method to segment the IMC on longitudinal B-mode ultrasound images. Our method consists of two stages: (i) extraction of the region of interest with a continuous max-flow algorithm and region-of-interest reconstruction using a stacked sparse auto-encoder model, and (ii) IMC segmentation using a trained random forest classifier. The proposed method has been tested on three databases from three different imaging centres, comprising a total of 228 ultrasound images of the common carotid artery. On the three databases, our method yields mean absolute errors of 0.028 ± 0.016 mm, 0.579 ± 0.288 pixel and 0.582 ± 0.341 pixel; polyline distance (PD) measures of 0.026 ± 0.017 mm, 0.657 ± 0.275 pixel and 0.731 ± 0:282 pixel; Hausdorff distance measures of 0.249 ± 0.101 mm, 4.760 ± 1.085 pixels and 5.825 ± 2.059 pixels; and correlation coefficients of 95.19%, 93.79%, and 98.96%, respectively. These results indicate that the proposed method performs well in segmentation of the IMC and measurement of the IMT. |
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